Recently a number of off-the-shelf methods for state-of-the-art triple extraction have emerged [1]}, but few of these systems work in multi-slot scenarios. Several groups [2]}, [3]} demonstrate multi-slot extraction using pre-trained embedding models such as BERT [4]}, but their systems are not publicly available. We recreate a similar system by framing the multi-slot extraction problem as a sequence labeling task where entity spans are labeled with a given slot name (e.g. SatelliteName, LaunchVehicle, etc.), and adapt an off-the-shelf BERT-based sequence labeling systemhttps://github.com/kamalkraj/BERT-NER to this task, which achieves near state-of-the-art performance on entity labeling tasks [5]}.
